Effects function analysis of ELF magnetic field exposure in the electric utility work environment.

The incomplete understanding of the relation between power-frequency fields and biological responses raises problems in defining an appropriate metric for exposure assessment and epidemiological studies. Based on evidence from biological experiments, one can define alternative metrics or effects functions that embody the relationship between field exposure patterns and hypothetical health effects. In this paper, we explore the application of the "effects function" approach to occupational exposure data. Our analysis provides examples of exposure assessments based on a range of plausible effects functions. An EMDEX time series data set of ELF frequency (40-800 Hz) magnetic field exposure measurements for electric utility workers was analyzed with several statistical measures and effects functions: average field strength, combination of threshold and exposure duration, and field strength changes. Results were compared for eight job categories: electrician, substation operator, machinist, welder, plant operator, lineman/splicer, meter reader, and clerical. Average field strength yields a different ranking for these job categories than the ranks obtained using other biologically plausible effects functions. Whereas the group of electricians has the highest exposure by average field strength, the group of substation operators has the highest ranking for most of the other effects functions. Plant operators rank highest in the total number of field strength changes greater than 1 microT per hour. The clerical group remains at the lowest end for all of these effects functions. Our analysis suggests that, although average field strength could be used as a surrogate of field exposure for simply classifying exposure into "low" and "high," this summary measure may be misleading in the relative ranking of job categories in which workers are in "high" fields. These results indicate the relevance of metrics other than average field strength in occupational exposure assessment and in the design and analysis of epidemiological studies.